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alibidaran/Gemma2_Farsi
Gemma2_Farsi is a text generation model from alibidaran. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
This model is Persian Q&A fine-tuned on Google's Gemma open-source model. Users can ask general question from it. It can be used for chatbot applications and fine-tuning for other datasets. - Developed by: Ali Bidaran…
Downloads · 30 days
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.safetensors5 GB · 100%
From the Hugging Face model README
This model is Persian Q&A fine-tuned on Google's Gemma open-source model. Users can ask general question from it. It can be used for chatbot applications and fine-tuning for other datasets.
This model can be used for developing chatbot applications, Q&A, instruction engineering and fine-tuning with other persian datasets.
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig, GemmaTokenizer
model_id = "alibidaran/Gemma2_Farsi"
bnb_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_quant_type="nf4",
bnb_4bit_compute_dtype=torch.bfloat16
)
tokenizer = AutoTokenizer.from_pretrained(model_id, token=os.environ['HF_TOKEN'])
model = AutoModelForCausalLM.from_pretrained(model_id, quantization_config=bnb_config, device_map={"":0}, token=os.environ['HF_TOKEN'])
prompt = "چند روش برای کاهش چربی بدن ارائه نمایید؟"
text = f"<s> ###Human: {prompt} ###Asistant: "
inputs=tokenizer(text,return_tensors='pt').to('cuda')
with torch.no_grad():
outputs=model.generate(**inputs,max_new_tokens=400,do_sample=True,top_p=0.99,top_k=10,temperature=0.7)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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